This page is about trend in personal consumption in the US
TODO: Add labels/titles;
Change colors;
Calculate percentage; Add animated Radar Area Chart;
Add description.
consumption_product = readxl::read_excel("data/consumption_product.xlsx") %>%
janitor::clean_names() %>%
pivot_longer(
x2019_q1 : x2021_q3,
names_to = "time",
names_prefix = "x",
values_to = "consumption"
)
consumption_function = readxl::read_excel("./data/consumption_function.xlsx") %>%
janitor::clean_names() %>%
filter(as.numeric(line) <= 28) %>%
pivot_longer(
x2019_q1 : x2021_q3,
names_to = "time",
names_prefix = "x",
values_to = "consumption"
) %>%
mutate(functions = recode(functions, `Household consumption expenditures (for services)` = "household",
`Final consumption expenditures of nonprofit institutions serving households (NPISHs)1` = "nonprofit consumption"))
general_1 = consumption_function %>%
filter(functions %in% c("Goods","Services"))
covid_seasonal = read_csv("covid_seasonal.csv") %>%
rename(time = date) %>%
select(time, quarterly)
consumption_seasonal = general_1 %>%
select(-line)
covid_consumption = left_join(consumption_seasonal, covid_seasonal, by = "time")
joint_plot = plot_ly(covid_consumption, x = ~time) %>%
add_trace(y = ~consumption, type = "scatter", mode = "lines", color = ~functions, yaixs = "y") %>%
add_trace(y = ~quarterly, type = "bar", name = "Covid Cases", yaxis = "y2") %>%
layout(yaxis=list(title = "consumption expenditure", side="left"),
yaxis2=list(title = "covid cases", side="right",overlaying="y"),
showlegend=TRUE)
joint_plot
general_2 = consumption_function %>%
filter(functions %in% c("Durable goods","Nondurable goods","household","nonprofit consumption")) %>%
select(-line) %>%
pivot_wider(names_from = functions, values_from = consumption) %>%
janitor::clean_names()
subfig_1 = plot_ly(general_2, x = ~time, y = ~durable_goods, type = "bar", name = "Durable Goods") %>%
add_trace(y = ~nondurable_goods, name = "Nondurable Goods") %>%
layout(yaxis = list(title = "Consumption"), barmode = "stack")
subfig_2 = plot_ly(general_2, x = ~time, y = ~household, type = "bar", name = "Household", colors = "Dark2") %>%
add_trace(y = ~nonprofit_consumption, name = "Nonprofit Consumption", colors = "Dark2") %>%
layout(yaixs = list(title = "Consumption"), barmode = "stack")
subfig_1
subfig_2
durable_goods =
consumption_function %>%
filter(functions %in% c("Motor vehicles and parts","Furnishings and durable household equipment","Recreational goods and vehicles","Other durable goods")) %>%
plot_ly(x = ~time, y = ~consumption, type = 'scatter', mode = 'lines', yaxis="y", color = ~functions) %>%
layout(legend = list(orientation = 'h', x = 0, y = -0.2))
nondurable_goods =
consumption_function %>%
filter(functions %in% c("Food and beverages purchased for off-premises consumption","Clothing and footwear","Gasoline and other energy goods","Other nondurable goods")) %>%
plot_ly(x = ~time, y = ~consumption, type = 'scatter', mode = 'lines', yaxis="y", color = ~functions) %>%
layout(legend = list(orientation = 'h', x = 0, y = -0.2))
household_consumption =
consumption_function %>%
filter(functions %in% c("Housing and utilities","Health care","Transportation services","Recreation services","Food services and accommodations","Financial services and insurance","Other services")) %>%
plot_ly(x = ~time, y = ~consumption, type = 'scatter', mode = 'lines', yaxis="y", color = ~functions) %>%
layout(legend = list(orientation = 'h', x = 0, y = -0.2))
durable_goods
nondurable_goods
household_consumption
fig <- plot_ly(
type = 'scatterpolar',
fill = 'toself'
)
fig <- fig %>%
add_trace(
r = c(39, 28, 8, 7, 28, 39),
theta = c('A','B','C', 'D', 'E', 'A'),
name = 'Group A'
)
fig <- fig %>%
add_trace(
r = c(1.5, 10, 39, 31, 15, 1.5),
theta = c('A','B','C', 'D', 'E', 'A'),
name = 'Group B'
)
fig <- fig %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,50)
)
)
)
fig